https://github.com/awrsha/kubeai-kubernetes-with-ai-analysis
A modern Kubernetes management dashboard with AI-powered analysis and insights.
https://github.com/awrsha/kubeai-kubernetes-with-ai-analysis
Last synced: 4 months ago
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A modern Kubernetes management dashboard with AI-powered analysis and insights.
- Host: GitHub
- URL: https://github.com/awrsha/kubeai-kubernetes-with-ai-analysis
- Owner: Awrsha
- License: mit
- Created: 2025-04-04T11:43:30.000Z (6 months ago)
- Default Branch: master
- Last Pushed: 2025-04-04T11:52:49.000Z (6 months ago)
- Last Synced: 2025-04-25T15:13:00.758Z (6 months ago)
- Language: HTML
- Size: 85 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# KubeAI 🚀
[](https://www.python.org)
[](https://flask.palletsprojects.com/)
[](https://kubernetes.io/)
[](https://groq.com/)
A modern Kubernetes management dashboard with AI-powered analysis and insights
## 🌟 Features
| Feature | Description |
|---------|-------------|
| 🔍 **Cluster Visualization** | Interactive dashboard showing pods, deployments, services, and nodes |
| 🤖 **AI Command Generator** | Natural language to kubectl command conversion |
| 🧠 **Anomaly Detection** | AI-powered detection of unusual cluster behavior |
| ⚡ **Optimization Recommendations** | Get AI-suggested performance improvements |
| 📊 **Resource Metrics** | Live CPU, memory, and storage usage monitoring |
| 📝 **Activity Logging** | Chronological record of cluster events |
## 📚 Technology Stack
- **Frontend**: HTML5, TailwindCSS, JavaScript
- **Backend**: Python, Flask
- **AI Integration**: GROQ API, Hugging Face Transformers
- **Kubernetes**: Official Python K8s Client
- **UI Design**: Inspired by Zoox and Apple design systems
## 🔧 Installation
### Prerequisites
- Python 3.8+
- Kubernetes cluster with configured `kubeconfig`
- API keys for GROQ and Hugging Face
### Setting up environment variables
```bash
export GROQ_API_KEY="your_groq_api_key"
export HUGGINGFACE_TOKEN="your_huggingface_token"
```
### Using pip
```bash
# Clone the repository
git clone https://github.com/Awrsha/KubeAI-Kubernetes-with-AI-Analysis.git
cd kubeai
# Install dependencies
pip install -r requirements.txt
# Run the application
python app.py
```
### Using Docker
```bash
# Build the image
docker build -t kubeai:latest .
# Run the container
docker run -p 5000:5000 \
-e GROQ_API_KEY="your_groq_api_key" \
-e HUGGINGFACE_TOKEN="your_huggingface_token" \
-v ~/.kube/config:/root/.kube/config \
kubeai:latest
```
## 🚀 Usage
After starting the application, navigate to `http://localhost:5000` in your web browser.
### AI Command Generator
Convert natural language to kubectl commands:
### Anomaly Detection
KubeAI automatically identifies potential issues in your cluster:
- **High CPU Usage**: Identifies pods consuming excessive CPU resources
- **Frequent Restarts**: Detects pods with abnormal restart patterns
- **Memory Leaks**: Identifies potential memory leaks in applications
- **Network Issues**: Detects unusual network traffic patterns or latency
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## 📝 License
This project is licensed under the MIT License - see the [LICENSE](https://poe.com/chat/LICENSE) file for details.
## 🙏 Acknowledgements
- [Kubernetes Python Client](https://github.com/kubernetes-client/python)
- [GROQ API](https://groq.com/) for AI text generation
- [Hugging Face](https://huggingface.co/) for AI model hosting
- [TailwindCSS](https://tailwindcss.com/) for the UI components
- [Flask](https://flask.palletsprojects.com/) for the web framework